{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 金融数据分析与建模\n",
    "\n",
    "## 课程内容\n",
    "\n",
    "https://github.com/stefan-jansen/machine-learning-for-trading\n",
    "\n",
    "* 机器学习,文本分析，神经网络\n",
    "* 量化策略\n",
    "\n",
    "## 现有的量化投资平台与数据获取\n",
    "\n",
    "* 聚宽，米筐，优矿，bigquant,掘金等等，现状，backtrader\n",
    "\n",
    "* 金融数据接口  akshare,tushare,baostock,掘金\n",
    "\n",
    "* 另外股票数据也可以一次性购买。淘宝拼多多100~200块能拿到所有历史数据，总大小也不过几个G，离线使用可以摆脱不少平台接口限制。缺点就是数据需要更新。\n",
    "\n",
    "https://zhuanlan.zhihu.com/p/219633414\n",
    "\n",
    "\n",
    "## AkShare \n",
    "\n",
    "AkShare 是基于 Python 的开源金融数据接口库，目的是实现对股票、期货、期权、基金、外汇、债券、指数、数字货币等金融产品的基本面数据、实时和历史行情数据、衍生数据从数据采集、数据清洗、到数据落地的一套开源工具，满足金融数据科学家，数据科学爱好者在金融数据获取方面的需求。\n",
    "\n",
    "AkShare 的特点是获取的是相对权威的金融数据网站公布的原始数据，广大数据科学家可以利用原始数据进行各数据源之间的交叉验证，进而再加工，从而得出科学的结论。\n",
    "\n",
    "## 一些库的安装\n",
    "\n",
    "外部数据源\n",
    "\n",
    "pip install akshare -i https://mirrors.aliyun.com/pypi/simple\n",
    "\n",
    "机器学习库\n",
    "\n",
    "pip install scikit-learn -i https://mirrors.aliyun.com/pypi/simple\n",
    "\n",
    "因子分析\n",
    "\n",
    "pip install alphalens -i https://mirrors.aliyun.com/pypi/simple\n",
    "\n",
    "可视化\n",
    "\n",
    "pip install pyecharts -i https://mirrors.aliyun.com/pypi/simple\n",
    "\n",
    "pip install seaborn -i https://mirrors.aliyun.com/pypi/simple\n",
    "\n",
    "回测框架\n",
    "\n",
    "pip install backtrader -i https://mirrors.aliyun.com/pypi/simple\n",
    "\n",
    "如果无法作图可能需要安装: backtrader[plotting]\n",
    "\n",
    "talib 量化指标（直接pip不行，需要用以下命令在终端安装）\n",
    "\n",
    "conda install -c conda-forge ta-lib\n",
    "\n",
    "\n",
    "### 数据的分类\n",
    "\n",
    "* 行情数据（股票随时间变化的价格，所有行情相关数据都是时间序列数据）\n",
    "* 财务数据（股票对应公司的财报数据）\n",
    "* 其他数据"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## classwork1\n",
    "\n",
    "安装 pyecharts，talib，导入这两个库并截图"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pyecharts\n",
    "import talib\n",
    "import backtrader as bt\n",
    "import alphalens as al\n",
    "import seaborn as sns\n",
    "import sklearn as sk\n",
    "import akshare as ak\n",
    "import pandas as pd"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 行情数据(单日数据)\n",
    "\n",
    "* 开盘收盘最高最低\n",
    "\n",
    "* 数据的精度\n",
    "\n",
    "* 前后复权\n",
    "\n",
    "https://www.akshare.xyz/index.html\n",
    "\n",
    "股票数据复权\n",
    "\n",
    "1.为何要复权：由于股票存在配股、分拆、合并和发放股息等事件，会导致股价出现较大的缺口。 若使用不复权的价格处理数据、计算各种指标，将会导致它们失去连续性，且使用不复权价格计算收益也会出现错误。 为了保证数据连贯性，常通过前复权和后复权对价格序列进行调整。\n",
    "\n",
    "2.前复权：保持当前价格不变，将历史价格进行增减，从而使股价连续。 前复权用来看盘非常方便，能一眼看出股价的历史走势，叠加各种技术指标也比较顺畅，是各种行情软件默认的复权方式。 这种方法虽然很常见，但也有两个缺陷需要注意。\n",
    "\n",
    "2.1 为了保证当前价格不变，每次股票除权除息，均需要重新调整历史价格，因此其历史价格是时变的。 这会导致在不同时点看到的历史前复权价可能出现差异。\n",
    "\n",
    "2.2 对于有持续分红的公司来说，前复权价可能出现负值。\n",
    "\n",
    "3.后复权：保证历史价格不变，在每次股票权益事件发生后，调整当前的股票价格。 后复权价格和真实股票价格可能差别较大，不适合用来看盘。 其优点在于，可以被看作投资者的长期财富增长曲线，反映投资者的真实收益率情况。\n",
    "\n",
    "4.在量化投资研究中普遍采用后复权数据。\n",
    "\n",
    "* 其他行情数据接口"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Help on function stock_zh_a_hist in module akshare.stock_feature.stock_hist_em:\n",
      "\n",
      "stock_zh_a_hist(symbol: str = '000001', period: str = 'daily', start_date: str = '19700101', end_date: str = '20500101', adjust: str = '') -> pandas.core.frame.DataFrame\n",
      "    东方财富网-行情首页-沪深京 A 股-每日行情\n",
      "    https://quote.eastmoney.com/concept/sh603777.html?from=classic\n",
      "    :param symbol: 股票代码\n",
      "    :type symbol: str\n",
      "    :param period: choice of {'daily', 'weekly', 'monthly'}\n",
      "    :type period: str\n",
      "    :param start_date: 开始日期\n",
      "    :type start_date: str\n",
      "    :param end_date: 结束日期\n",
      "    :type end_date: str\n",
      "    :param adjust: choice of {\"qfq\": \"前复权\", \"hfq\": \"后复权\", \"\": \"不复权\"}\n",
      "    :type adjust: str\n",
      "    :return: 每日行情\n",
      "    :rtype: pandas.DataFrame\n",
      "\n"
     ]
    }
   ],
   "source": [
    "help(ak.stock_zh_a_hist)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "              日期     开盘     收盘     最高     最低      成交量           成交额    振幅  \\\n",
      "0     2017-03-01   9.49   9.49   9.55   9.47   346994  3.301580e+08  0.84   \n",
      "1     2017-03-02   9.51   9.43   9.54   9.42   403629  3.823959e+08  1.26   \n",
      "2     2017-03-03   9.41   9.40   9.43   9.36   342655  3.219525e+08  0.74   \n",
      "3     2017-03-06   9.40   9.45   9.46   9.39   404511  3.812123e+08  0.74   \n",
      "4     2017-03-07   9.44   9.45   9.46   9.40   294673  2.777474e+08  0.63   \n",
      "...          ...    ...    ...    ...    ...      ...           ...   ...   \n",
      "1439  2023-02-01  15.03  14.70  15.08  14.51  1653421  2.426472e+09  3.80   \n",
      "1440  2023-02-02  14.74  14.60  14.78  14.27  1577900  2.280745e+09  3.47   \n",
      "1441  2023-02-03  14.45  14.32  14.55  14.16  1246383  1.782106e+09  2.67   \n",
      "1442  2023-02-06  14.10  14.00  14.13  13.86  1317610  1.838429e+09  1.89   \n",
      "1443  2023-02-07  14.06  14.21  14.32  14.03   869460  1.235298e+09  2.07   \n",
      "\n",
      "       涨跌幅   涨跌额   换手率  \n",
      "0     0.11  0.01  0.21  \n",
      "1    -0.63 -0.06  0.24  \n",
      "2    -0.32 -0.03  0.20  \n",
      "3     0.53  0.05  0.24  \n",
      "4     0.00  0.00  0.17  \n",
      "...    ...   ...   ...  \n",
      "1439 -1.93 -0.29  0.85  \n",
      "1440 -0.68 -0.10  0.81  \n",
      "1441 -1.92 -0.28  0.64  \n",
      "1442 -2.23 -0.32  0.68  \n",
      "1443  1.50  0.21  0.45  \n",
      "\n",
      "[1444 rows x 11 columns]\n"
     ]
    }
   ],
   "source": [
    "#中国平安 股票代码：000001\n",
    "#注意不复权与复权的区别\n",
    "stock_pinan = ak.stock_zh_a_hist(symbol=\"000001\", period=\"daily\", start_date=\"20170301\", end_date='20230207', adjust=\"\")\n",
    "print(stock_pinan)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "\n",
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       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>日期</th>\n",
       "      <th>开盘</th>\n",
       "      <th>收盘</th>\n",
       "      <th>最高</th>\n",
       "      <th>最低</th>\n",
       "      <th>成交量</th>\n",
       "      <th>成交额</th>\n",
       "      <th>振幅</th>\n",
       "      <th>涨跌幅</th>\n",
       "      <th>涨跌额</th>\n",
       "      <th>换手率</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2017-03-01</td>\n",
       "      <td>9.49</td>\n",
       "      <td>9.49</td>\n",
       "      <td>9.55</td>\n",
       "      <td>9.47</td>\n",
       "      <td>346994</td>\n",
       "      <td>3.301580e+08</td>\n",
       "      <td>0.84</td>\n",
       "      <td>0.11</td>\n",
       "      <td>0.01</td>\n",
       "      <td>0.21</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2017-03-02</td>\n",
       "      <td>9.51</td>\n",
       "      <td>9.43</td>\n",
       "      <td>9.54</td>\n",
       "      <td>9.42</td>\n",
       "      <td>403629</td>\n",
       "      <td>3.823959e+08</td>\n",
       "      <td>1.26</td>\n",
       "      <td>-0.63</td>\n",
       "      <td>-0.06</td>\n",
       "      <td>0.24</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2017-03-03</td>\n",
       "      <td>9.41</td>\n",
       "      <td>9.40</td>\n",
       "      <td>9.43</td>\n",
       "      <td>9.36</td>\n",
       "      <td>342655</td>\n",
       "      <td>3.219525e+08</td>\n",
       "      <td>0.74</td>\n",
       "      <td>-0.32</td>\n",
       "      <td>-0.03</td>\n",
       "      <td>0.20</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2017-03-06</td>\n",
       "      <td>9.40</td>\n",
       "      <td>9.45</td>\n",
       "      <td>9.46</td>\n",
       "      <td>9.39</td>\n",
       "      <td>404511</td>\n",
       "      <td>3.812123e+08</td>\n",
       "      <td>0.74</td>\n",
       "      <td>0.53</td>\n",
       "      <td>0.05</td>\n",
       "      <td>0.24</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2017-03-07</td>\n",
       "      <td>9.44</td>\n",
       "      <td>9.45</td>\n",
       "      <td>9.46</td>\n",
       "      <td>9.40</td>\n",
       "      <td>294673</td>\n",
       "      <td>2.777474e+08</td>\n",
       "      <td>0.63</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.17</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1439</th>\n",
       "      <td>2023-02-01</td>\n",
       "      <td>15.03</td>\n",
       "      <td>14.70</td>\n",
       "      <td>15.08</td>\n",
       "      <td>14.51</td>\n",
       "      <td>1653421</td>\n",
       "      <td>2.426472e+09</td>\n",
       "      <td>3.80</td>\n",
       "      <td>-1.93</td>\n",
       "      <td>-0.29</td>\n",
       "      <td>0.85</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1440</th>\n",
       "      <td>2023-02-02</td>\n",
       "      <td>14.74</td>\n",
       "      <td>14.60</td>\n",
       "      <td>14.78</td>\n",
       "      <td>14.27</td>\n",
       "      <td>1577900</td>\n",
       "      <td>2.280745e+09</td>\n",
       "      <td>3.47</td>\n",
       "      <td>-0.68</td>\n",
       "      <td>-0.10</td>\n",
       "      <td>0.81</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1441</th>\n",
       "      <td>2023-02-03</td>\n",
       "      <td>14.45</td>\n",
       "      <td>14.32</td>\n",
       "      <td>14.55</td>\n",
       "      <td>14.16</td>\n",
       "      <td>1246383</td>\n",
       "      <td>1.782106e+09</td>\n",
       "      <td>2.67</td>\n",
       "      <td>-1.92</td>\n",
       "      <td>-0.28</td>\n",
       "      <td>0.64</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1442</th>\n",
       "      <td>2023-02-06</td>\n",
       "      <td>14.10</td>\n",
       "      <td>14.00</td>\n",
       "      <td>14.13</td>\n",
       "      <td>13.86</td>\n",
       "      <td>1317610</td>\n",
       "      <td>1.838429e+09</td>\n",
       "      <td>1.89</td>\n",
       "      <td>-2.23</td>\n",
       "      <td>-0.32</td>\n",
       "      <td>0.68</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1443</th>\n",
       "      <td>2023-02-07</td>\n",
       "      <td>14.06</td>\n",
       "      <td>14.21</td>\n",
       "      <td>14.32</td>\n",
       "      <td>14.03</td>\n",
       "      <td>869460</td>\n",
       "      <td>1.235298e+09</td>\n",
       "      <td>2.07</td>\n",
       "      <td>1.50</td>\n",
       "      <td>0.21</td>\n",
       "      <td>0.45</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>1444 rows × 11 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "              日期     开盘     收盘     最高     最低      成交量           成交额    振幅  \\\n",
       "0     2017-03-01   9.49   9.49   9.55   9.47   346994  3.301580e+08  0.84   \n",
       "1     2017-03-02   9.51   9.43   9.54   9.42   403629  3.823959e+08  1.26   \n",
       "2     2017-03-03   9.41   9.40   9.43   9.36   342655  3.219525e+08  0.74   \n",
       "3     2017-03-06   9.40   9.45   9.46   9.39   404511  3.812123e+08  0.74   \n",
       "4     2017-03-07   9.44   9.45   9.46   9.40   294673  2.777474e+08  0.63   \n",
       "...          ...    ...    ...    ...    ...      ...           ...   ...   \n",
       "1439  2023-02-01  15.03  14.70  15.08  14.51  1653421  2.426472e+09  3.80   \n",
       "1440  2023-02-02  14.74  14.60  14.78  14.27  1577900  2.280745e+09  3.47   \n",
       "1441  2023-02-03  14.45  14.32  14.55  14.16  1246383  1.782106e+09  2.67   \n",
       "1442  2023-02-06  14.10  14.00  14.13  13.86  1317610  1.838429e+09  1.89   \n",
       "1443  2023-02-07  14.06  14.21  14.32  14.03   869460  1.235298e+09  2.07   \n",
       "\n",
       "       涨跌幅   涨跌额   换手率  \n",
       "0     0.11  0.01  0.21  \n",
       "1    -0.63 -0.06  0.24  \n",
       "2    -0.32 -0.03  0.20  \n",
       "3     0.53  0.05  0.24  \n",
       "4     0.00  0.00  0.17  \n",
       "...    ...   ...   ...  \n",
       "1439 -1.93 -0.29  0.85  \n",
       "1440 -0.68 -0.10  0.81  \n",
       "1441 -1.92 -0.28  0.64  \n",
       "1442 -2.23 -0.32  0.68  \n",
       "1443  1.50  0.21  0.45  \n",
       "\n",
       "[1444 rows x 11 columns]"
      ]
     },
     "execution_count": 37,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "stock_pinan"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 数据的选择与切片\n",
    "\n",
    "* 显式索引，顺序索引\n",
    "\n",
    "* 简单作图"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [],
   "source": [
    "stock_pinan.set_index(\"日期\",inplace=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>开盘</th>\n",
       "      <th>收盘</th>\n",
       "      <th>最高</th>\n",
       "      <th>最低</th>\n",
       "      <th>成交量</th>\n",
       "      <th>成交额</th>\n",
       "      <th>振幅</th>\n",
       "      <th>涨跌幅</th>\n",
       "      <th>涨跌额</th>\n",
       "      <th>换手率</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>日期</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2017-03-01</th>\n",
       "      <td>9.49</td>\n",
       "      <td>9.49</td>\n",
       "      <td>9.55</td>\n",
       "      <td>9.47</td>\n",
       "      <td>346994</td>\n",
       "      <td>3.301580e+08</td>\n",
       "      <td>0.84</td>\n",
       "      <td>0.11</td>\n",
       "      <td>0.01</td>\n",
       "      <td>0.21</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-03-02</th>\n",
       "      <td>9.51</td>\n",
       "      <td>9.43</td>\n",
       "      <td>9.54</td>\n",
       "      <td>9.42</td>\n",
       "      <td>403629</td>\n",
       "      <td>3.823959e+08</td>\n",
       "      <td>1.26</td>\n",
       "      <td>-0.63</td>\n",
       "      <td>-0.06</td>\n",
       "      <td>0.24</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-03-03</th>\n",
       "      <td>9.41</td>\n",
       "      <td>9.40</td>\n",
       "      <td>9.43</td>\n",
       "      <td>9.36</td>\n",
       "      <td>342655</td>\n",
       "      <td>3.219525e+08</td>\n",
       "      <td>0.74</td>\n",
       "      <td>-0.32</td>\n",
       "      <td>-0.03</td>\n",
       "      <td>0.20</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-03-06</th>\n",
       "      <td>9.40</td>\n",
       "      <td>9.45</td>\n",
       "      <td>9.46</td>\n",
       "      <td>9.39</td>\n",
       "      <td>404511</td>\n",
       "      <td>3.812123e+08</td>\n",
       "      <td>0.74</td>\n",
       "      <td>0.53</td>\n",
       "      <td>0.05</td>\n",
       "      <td>0.24</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-03-07</th>\n",
       "      <td>9.44</td>\n",
       "      <td>9.45</td>\n",
       "      <td>9.46</td>\n",
       "      <td>9.40</td>\n",
       "      <td>294673</td>\n",
       "      <td>2.777474e+08</td>\n",
       "      <td>0.63</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.17</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2023-02-01</th>\n",
       "      <td>15.03</td>\n",
       "      <td>14.70</td>\n",
       "      <td>15.08</td>\n",
       "      <td>14.51</td>\n",
       "      <td>1653421</td>\n",
       "      <td>2.426472e+09</td>\n",
       "      <td>3.80</td>\n",
       "      <td>-1.93</td>\n",
       "      <td>-0.29</td>\n",
       "      <td>0.85</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2023-02-02</th>\n",
       "      <td>14.74</td>\n",
       "      <td>14.60</td>\n",
       "      <td>14.78</td>\n",
       "      <td>14.27</td>\n",
       "      <td>1577900</td>\n",
       "      <td>2.280745e+09</td>\n",
       "      <td>3.47</td>\n",
       "      <td>-0.68</td>\n",
       "      <td>-0.10</td>\n",
       "      <td>0.81</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2023-02-03</th>\n",
       "      <td>14.45</td>\n",
       "      <td>14.32</td>\n",
       "      <td>14.55</td>\n",
       "      <td>14.16</td>\n",
       "      <td>1246383</td>\n",
       "      <td>1.782106e+09</td>\n",
       "      <td>2.67</td>\n",
       "      <td>-1.92</td>\n",
       "      <td>-0.28</td>\n",
       "      <td>0.64</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2023-02-06</th>\n",
       "      <td>14.10</td>\n",
       "      <td>14.00</td>\n",
       "      <td>14.13</td>\n",
       "      <td>13.86</td>\n",
       "      <td>1317610</td>\n",
       "      <td>1.838429e+09</td>\n",
       "      <td>1.89</td>\n",
       "      <td>-2.23</td>\n",
       "      <td>-0.32</td>\n",
       "      <td>0.68</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2023-02-07</th>\n",
       "      <td>14.06</td>\n",
       "      <td>14.21</td>\n",
       "      <td>14.32</td>\n",
       "      <td>14.03</td>\n",
       "      <td>869460</td>\n",
       "      <td>1.235298e+09</td>\n",
       "      <td>2.07</td>\n",
       "      <td>1.50</td>\n",
       "      <td>0.21</td>\n",
       "      <td>0.45</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>1444 rows × 10 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "               开盘     收盘     最高     最低      成交量           成交额    振幅   涨跌幅  \\\n",
       "日期                                                                          \n",
       "2017-03-01   9.49   9.49   9.55   9.47   346994  3.301580e+08  0.84  0.11   \n",
       "2017-03-02   9.51   9.43   9.54   9.42   403629  3.823959e+08  1.26 -0.63   \n",
       "2017-03-03   9.41   9.40   9.43   9.36   342655  3.219525e+08  0.74 -0.32   \n",
       "2017-03-06   9.40   9.45   9.46   9.39   404511  3.812123e+08  0.74  0.53   \n",
       "2017-03-07   9.44   9.45   9.46   9.40   294673  2.777474e+08  0.63  0.00   \n",
       "...           ...    ...    ...    ...      ...           ...   ...   ...   \n",
       "2023-02-01  15.03  14.70  15.08  14.51  1653421  2.426472e+09  3.80 -1.93   \n",
       "2023-02-02  14.74  14.60  14.78  14.27  1577900  2.280745e+09  3.47 -0.68   \n",
       "2023-02-03  14.45  14.32  14.55  14.16  1246383  1.782106e+09  2.67 -1.92   \n",
       "2023-02-06  14.10  14.00  14.13  13.86  1317610  1.838429e+09  1.89 -2.23   \n",
       "2023-02-07  14.06  14.21  14.32  14.03   869460  1.235298e+09  2.07  1.50   \n",
       "\n",
       "             涨跌额   换手率  \n",
       "日期                      \n",
       "2017-03-01  0.01  0.21  \n",
       "2017-03-02 -0.06  0.24  \n",
       "2017-03-03 -0.03  0.20  \n",
       "2017-03-06  0.05  0.24  \n",
       "2017-03-07  0.00  0.17  \n",
       "...          ...   ...  \n",
       "2023-02-01 -0.29  0.85  \n",
       "2023-02-02 -0.10  0.81  \n",
       "2023-02-03 -0.28  0.64  \n",
       "2023-02-06 -0.32  0.68  \n",
       "2023-02-07  0.21  0.45  \n",
       "\n",
       "[1444 rows x 10 columns]"
      ]
     },
     "execution_count": 39,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "stock_pinan"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [],
   "source": [
    "from matplotlib import rcParams\n",
    "rcParams['font.family'] = 'SimHei'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 51,
   "metadata": {},
   "outputs": [],
   "source": [
    "#help(stock_pinan.loc[\"2021-05-15\":\"2023-01-20\",[\"最高\",\"最低\"]].plot)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 50,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:xlabel='日期'>"
      ]
     },
     "execution_count": 50,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 720x360 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "stock_pinan.loc[\"2021-05-15\":\"2023-01-20\",[\"最高\",\"最低\"]].plot(style=\"-\",figsize=(10,5),rot=30,grid=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "日期\n",
       "2017-03-01     9.55\n",
       "2017-03-02     9.54\n",
       "2017-03-03     9.43\n",
       "2017-03-06     9.46\n",
       "2017-03-07     9.46\n",
       "              ...  \n",
       "2023-02-01    15.08\n",
       "2023-02-02    14.78\n",
       "2023-02-03    14.55\n",
       "2023-02-06    14.13\n",
       "2023-02-07    14.32\n",
       "Name: 最高, Length: 1444, dtype: float64"
      ]
     },
     "execution_count": 41,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "stock_pinan[\"最高\"]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## classwork 2\n",
    "\n",
    "* 读入 sh600050 中国联通的历史行情数据\n",
    "\n",
    "* 做出2019年中国联通的每日开盘和收盘价的曲线图"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 基于pyecharts的k线图\n",
    "\n",
    "\n",
    "更多的例子：\n",
    "\n",
    "https://gallery.pyecharts.org/#/Candlestick/README\n",
    "\n",
    "* k线图的基本意义\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'1.8.1'"
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pyecharts.__version__"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 52,
   "metadata": {},
   "outputs": [],
   "source": [
    "## 官网例子\n",
    "from pyecharts import options as opts\n",
    "from pyecharts.charts import Kline\n",
    "\n",
    "data = [\n",
    "    [2320.26, 2320.26, 2287.3, 2362.94],\n",
    "    [2300, 2291.3, 2288.26, 2308.38],\n",
    "    [2295.35, 2346.5, 2295.35, 2345.92],\n",
    "    [2347.22, 2358.98, 2337.35, 2363.8],\n",
    "    [2360.75, 2382.48, 2347.89, 2383.76],\n",
    "    [2383.43, 2385.42, 2371.23, 2391.82],\n",
    "    [2377.41, 2419.02, 2369.57, 2421.15],\n",
    "    [2425.92, 2428.15, 2417.58, 2440.38],\n",
    "    [2411, 2433.13, 2403.3, 2437.42],\n",
    "    [2432.68, 2334.48, 2427.7, 2441.73],\n",
    "    [2430.69, 2418.53, 2394.22, 2433.89],\n",
    "    [2416.62, 2432.4, 2414.4, 2443.03],\n",
    "    [2441.91, 2421.56, 2418.43, 2444.8],\n",
    "    [2420.26, 2382.91, 2373.53, 2427.07],\n",
    "    [2383.49, 2397.18, 2370.61, 2397.94],\n",
    "    [2378.82, 2325.95, 2309.17, 2378.82],\n",
    "    [2322.94, 2314.16, 2308.76, 2330.88],\n",
    "    [2320.62, 2325.82, 2315.01, 2338.78],\n",
    "    [2313.74, 2293.34, 2289.89, 2340.71],\n",
    "    [2297.77, 2313.22, 2292.03, 2324.63],\n",
    "    [2322.32, 2365.59, 2308.92, 2366.16],\n",
    "    [2364.54, 2359.51, 2330.86, 2369.65],\n",
    "    [2332.08, 2273.4, 2259.25, 2333.54],\n",
    "    [2274.81, 2326.31, 2270.1, 2328.14],\n",
    "    [2333.61, 2347.18, 2321.6, 2351.44],\n",
    "    [2340.44, 2324.29, 2304.27, 2352.02],\n",
    "    [2326.42, 2318.61, 2314.59, 2333.67],\n",
    "    [2314.68, 2310.59, 2296.58, 2320.96],\n",
    "    [2309.16, 2286.6, 2264.83, 2333.29],\n",
    "    [2282.17, 2263.97, 2253.25, 2286.33],\n",
    "    [2255.77, 2270.28, 2253.31, 2276.22],\n",
    "]\n",
    "\n",
    "\n",
    "c = (\n",
    "    Kline()\n",
    "    .add_xaxis([\"2017/7/{}\".format(i + 1) for i in range(31)])\n",
    "    .add_yaxis(\"kline\", data)\n",
    "    .set_global_opts(\n",
    "        yaxis_opts=opts.AxisOpts(is_scale=True),\n",
    "        xaxis_opts=opts.AxisOpts(is_scale=True),\n",
    "        title_opts=opts.TitleOpts(title=\"Kline-基本示例\"),\n",
    "    )\n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 53,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "\n",
       "<script>\n",
       "    require.config({\n",
       "        paths: {\n",
       "            'echarts':'https://assets.pyecharts.org/assets/echarts.min'\n",
       "        }\n",
       "    });\n",
       "</script>\n",
       "\n",
       "        <div id=\"68366595fe1c43bb9e63aa91039c751b\" style=\"width:900px; height:500px;\"></div>\n",
       "\n",
       "<script>\n",
       "        require(['echarts'], function(echarts) {\n",
       "                var chart_68366595fe1c43bb9e63aa91039c751b = echarts.init(\n",
       "                    document.getElementById('68366595fe1c43bb9e63aa91039c751b'), 'white', {renderer: 'canvas'});\n",
       "                var option_68366595fe1c43bb9e63aa91039c751b = {\n",
       "    \"animation\": true,\n",
       "    \"animationThreshold\": 2000,\n",
       "    \"animationDuration\": 1000,\n",
       "    \"animationEasing\": \"cubicOut\",\n",
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       "    \"animationEasingUpdate\": \"cubicOut\",\n",
       "    \"animationDelayUpdate\": 0,\n",
       "    \"color\": [\n",
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       "    \"legend\": [\n",
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       "            \"data\": [\n",
       "                \"kline\"\n",
       "            ],\n",
       "            \"selected\": {\n",
       "                \"kline\": true\n",
       "            },\n",
       "            \"show\": true,\n",
       "            \"padding\": 5,\n",
       "            \"itemGap\": 10,\n",
       "            \"itemWidth\": 25,\n",
       "            \"itemHeight\": 14\n",
       "        }\n",
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       "    \"tooltip\": {\n",
       "        \"show\": true,\n",
       "        \"trigger\": \"item\",\n",
       "        \"triggerOn\": \"mousemove|click\",\n",
       "        \"axisPointer\": {\n",
       "            \"type\": \"line\"\n",
       "        },\n",
       "        \"showContent\": true,\n",
       "        \"alwaysShowContent\": false,\n",
       "        \"showDelay\": 0,\n",
       "        \"hideDelay\": 100,\n",
       "        \"textStyle\": {\n",
       "            \"fontSize\": 14\n",
       "        },\n",
       "        \"borderWidth\": 0,\n",
       "        \"padding\": 5\n",
       "    },\n",
       "    \"xAxis\": [\n",
       "        {\n",
       "            \"show\": true,\n",
       "            \"scale\": true,\n",
       "            \"nameLocation\": \"end\",\n",
       "            \"nameGap\": 15,\n",
       "            \"gridIndex\": 0,\n",
       "            \"inverse\": false,\n",
       "            \"offset\": 0,\n",
       "            \"splitNumber\": 5,\n",
       "            \"minInterval\": 0,\n",
       "            \"splitLine\": {\n",
       "                \"show\": false,\n",
       "                \"lineStyle\": {\n",
       "                    \"show\": true,\n",
       "                    \"width\": 1,\n",
       "                    \"opacity\": 1,\n",
       "                    \"curveness\": 0,\n",
       "                    \"type\": \"solid\"\n",
       "                }\n",
       "            },\n",
       "            \"data\": [\n",
       "                \"2017/7/1\",\n",
       "                \"2017/7/2\",\n",
       "                \"2017/7/3\",\n",
       "                \"2017/7/4\",\n",
       "                \"2017/7/5\",\n",
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       "                \"2017/7/11\",\n",
       "                \"2017/7/12\",\n",
       "                \"2017/7/13\",\n",
       "                \"2017/7/14\",\n",
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       "                \"2017/7/16\",\n",
       "                \"2017/7/17\",\n",
       "                \"2017/7/18\",\n",
       "                \"2017/7/19\",\n",
       "                \"2017/7/20\",\n",
       "                \"2017/7/21\",\n",
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       "                \"2017/7/25\",\n",
       "                \"2017/7/26\",\n",
       "                \"2017/7/27\",\n",
       "                \"2017/7/28\",\n",
       "                \"2017/7/29\",\n",
       "                \"2017/7/30\",\n",
       "                \"2017/7/31\"\n",
       "            ]\n",
       "        }\n",
       "    ],\n",
       "    \"yAxis\": [\n",
       "        {\n",
       "            \"show\": true,\n",
       "            \"scale\": true,\n",
       "            \"nameLocation\": \"end\",\n",
       "            \"nameGap\": 15,\n",
       "            \"gridIndex\": 0,\n",
       "            \"inverse\": false,\n",
       "            \"offset\": 0,\n",
       "            \"splitNumber\": 5,\n",
       "            \"minInterval\": 0,\n",
       "            \"splitLine\": {\n",
       "                \"show\": false,\n",
       "                \"lineStyle\": {\n",
       "                    \"show\": true,\n",
       "                    \"width\": 1,\n",
       "                    \"opacity\": 1,\n",
       "                    \"curveness\": 0,\n",
       "                    \"type\": \"solid\"\n",
       "                }\n",
       "            }\n",
       "        }\n",
       "    ],\n",
       "    \"title\": [\n",
       "        {\n",
       "            \"text\": \"Kline-\\u57fa\\u672c\\u793a\\u4f8b\",\n",
       "            \"padding\": 5,\n",
       "            \"itemGap\": 10\n",
       "        }\n",
       "    ]\n",
       "};\n",
       "                chart_68366595fe1c43bb9e63aa91039c751b.setOption(option_68366595fe1c43bb9e63aa91039c751b);\n",
       "        });\n",
       "    </script>\n"
      ],
      "text/plain": [
       "<pyecharts.render.display.HTML at 0x253762c6280>"
      ]
     },
     "execution_count": 53,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "c=Kline()\n",
    "c.add_xaxis([\"2017/7/{}\".format(i + 1) for i in range(31)])\n",
    "c.add_yaxis(\"kline\", data)\n",
    "c.set_global_opts(\n",
    "        title_opts=opts.TitleOpts(title=\"Kline-基本示例\"),\n",
    "    )\n",
    "c.render_notebook()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [],
   "source": [
    "#[\"2017/7/{}\".format(i + 1) for i in range(31)]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "    },\n",
       "    \"xAxis\": [\n",
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       "                \"2017/7/14\",\n",
       "                \"2017/7/15\",\n",
       "                \"2017/7/16\",\n",
       "                \"2017/7/17\",\n",
       "                \"2017/7/18\",\n",
       "                \"2017/7/19\",\n",
       "                \"2017/7/20\",\n",
       "                \"2017/7/21\",\n",
       "                \"2017/7/22\",\n",
       "                \"2017/7/23\",\n",
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       "                \"2017/7/26\",\n",
       "                \"2017/7/27\",\n",
       "                \"2017/7/28\",\n",
       "                \"2017/7/29\",\n",
       "                \"2017/7/30\",\n",
       "                \"2017/7/31\"\n",
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       "        }\n",
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       "    \"yAxis\": [\n",
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   "cell_type": "code",
   "execution_count": 71,
   "metadata": {},
   "outputs": [],
   "source": [
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   "execution_count": 72,
   "metadata": {},
   "outputs": [
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       "      <th>2020-01-09</th>\n",
       "      <td>16.81</td>\n",
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       "      <td>16.79</td>\n",
       "      <td>16.69</td>\n",
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       "    <tr>\n",
       "      <th>2020-01-13</th>\n",
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       "      <td>17.03</td>\n",
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       "               开盘     收盘     最高     最低\n",
       "日期                                    \n",
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       "2020-01-10  16.79  16.69  16.81  16.52\n",
       "2020-01-13  16.75  16.99  17.03  16.61\n",
       "2020-01-14  16.99  16.76  17.27  16.76\n",
       "2020-01-15  16.79  16.52  16.86  16.45\n",
       "2020-01-16  16.52  16.33  16.57  16.20\n",
       "2020-01-17  16.38  16.39  16.55  16.35\n",
       "2020-01-20  16.43  16.45  16.61  16.35\n",
       "2020-01-21  16.34  16.00  16.34  15.93\n",
       "2020-01-22  15.92  16.09  16.16  15.71\n",
       "2020-01-23  15.92  15.54  15.92  15.39\n",
       "2020-02-03  13.99  13.99  14.70  13.99\n",
       "2020-02-04  14.05  14.60  14.66  14.02\n",
       "2020-02-05  14.59  14.63  14.89  14.32\n",
       "2020-02-06  14.81  14.77  14.87  14.51\n",
       "2020-02-07  14.60  14.62  14.69  14.41"
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    "data1"
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  {
   "cell_type": "code",
   "execution_count": 73,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['2020-01-09',\n",
       " '2020-01-10',\n",
       " '2020-01-13',\n",
       " '2020-01-14',\n",
       " '2020-01-15',\n",
       " '2020-01-16',\n",
       " '2020-01-17',\n",
       " '2020-01-20',\n",
       " '2020-01-21',\n",
       " '2020-01-22',\n",
       " '2020-01-23',\n",
       " '2020-02-03',\n",
       " '2020-02-04',\n",
       " '2020-02-05',\n",
       " '2020-02-06',\n",
       " '2020-02-07']"
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     "metadata": {},
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   "execution_count": 74,
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       " [16.99, 16.76, 17.27, 16.76],\n",
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       " [16.38, 16.39, 16.55, 16.35],\n",
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       " [16.34, 16.0, 16.34, 15.93],\n",
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       " [14.59, 14.63, 14.89, 14.32],\n",
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   "execution_count": 75,
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     "execution_count": 75,
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    "c=Kline()\n",
    "c.add_xaxis(data1.index.tolist())\n",
    "c.add_yaxis(\"kline\", data1.values.tolist(),itemstyle_opts=opts.ItemStyleOpts(color=\"pink\", color0=\"black\"))\n",
    "c.set_global_opts(datazoom_opts=[opts.DataZoomOpts(type_=\"inside\"),opts.DataZoomOpts(type_=\"slider\")]\n",
    "    )\n",
    "c.render_notebook()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 76,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "\n",
       "<script>\n",
       "    require.config({\n",
       "        paths: {\n",
       "            'echarts':'https://assets.pyecharts.org/assets/echarts.min'\n",
       "        }\n",
       "    });\n",
       "</script>\n",
       "\n",
       "        <div id=\"cbf5d8c7dd0c4577916bf2b7aa849a0d\" style=\"width:900px; height:500px;\"></div>\n",
       "\n",
       "<script>\n",
       "        require(['echarts'], function(echarts) {\n",
       "                var chart_cbf5d8c7dd0c4577916bf2b7aa849a0d = echarts.init(\n",
       "                    document.getElementById('cbf5d8c7dd0c4577916bf2b7aa849a0d'), 'white', {renderer: 'canvas'});\n",
       "                var option_cbf5d8c7dd0c4577916bf2b7aa849a0d = {\n",
       "    \"animation\": true,\n",
       "    \"animationThreshold\": 2000,\n",
       "    \"animationDuration\": 1000,\n",
       "    \"animationEasing\": \"cubicOut\",\n",
       "    \"animationDelay\": 0,\n",
       "    \"animationDurationUpdate\": 300,\n",
       "    \"animationEasingUpdate\": \"cubicOut\",\n",
       "    \"animationDelayUpdate\": 0,\n",
       "    \"color\": [\n",
       "        \"#c23531\",\n",
       "        \"#2f4554\",\n",
       "        \"#61a0a8\",\n",
       "        \"#d48265\",\n",
       "        \"#749f83\",\n",
       "        \"#ca8622\",\n",
       "        \"#bda29a\",\n",
       "        \"#6e7074\",\n",
       "        \"#546570\",\n",
       "        \"#c4ccd3\",\n",
       "        \"#f05b72\",\n",
       "        \"#ef5b9c\",\n",
       "        \"#f47920\",\n",
       "        \"#905a3d\",\n",
       "        \"#fab27b\",\n",
       "        \"#2a5caa\",\n",
       "        \"#444693\",\n",
       "        \"#726930\",\n",
       "        \"#b2d235\",\n",
       "        \"#6d8346\",\n",
       "        \"#ac6767\",\n",
       "        \"#1d953f\",\n",
       "        \"#6950a1\",\n",
       "        \"#918597\"\n",
       "    ],\n",
       "    \"series\": [\n",
       "        {\n",
       "            \"type\": \"candlestick\",\n",
       "            \"name\": \"kline\",\n",
       "            \"data\": [\n",
       "                [\n",
       "                    16.81,\n",
       "                    16.79,\n",
       "                    16.93,\n",
       "                    16.53\n",
       "                ],\n",
       "                [\n",
       "                    16.79,\n",
       "                    16.69,\n",
       "                    16.81,\n",
       "                    16.52\n",
       "                ],\n",
       "                [\n",
       "                    16.75,\n",
       "                    16.99,\n",
       "                    17.03,\n",
       "                    16.61\n",
       "                ],\n",
       "                [\n",
       "                    16.99,\n",
       "                    16.76,\n",
       "                    17.27,\n",
       "                    16.76\n",
       "                ],\n",
       "                [\n",
       "                    16.79,\n",
       "                    16.52,\n",
       "                    16.86,\n",
       "                    16.45\n",
       "                ],\n",
       "                [\n",
       "                    16.52,\n",
       "                    16.33,\n",
       "                    16.57,\n",
       "                    16.2\n",
       "                ],\n",
       "                [\n",
       "                    16.38,\n",
       "                    16.39,\n",
       "                    16.55,\n",
       "                    16.35\n",
       "                ],\n",
       "                [\n",
       "                    16.43,\n",
       "                    16.45,\n",
       "                    16.61,\n",
       "                    16.35\n",
       "                ],\n",
       "                [\n",
       "                    16.34,\n",
       "                    16.0,\n",
       "                    16.34,\n",
       "                    15.93\n",
       "                ],\n",
       "                [\n",
       "                    15.92,\n",
       "                    16.09,\n",
       "                    16.16,\n",
       "                    15.71\n",
       "                ],\n",
       "                [\n",
       "                    15.92,\n",
       "                    15.54,\n",
       "                    15.92,\n",
       "                    15.39\n",
       "                ],\n",
       "                [\n",
       "                    13.99,\n",
       "                    13.99,\n",
       "                    14.7,\n",
       "                    13.99\n",
       "                ],\n",
       "                [\n",
       "                    14.05,\n",
       "                    14.6,\n",
       "                    14.66,\n",
       "                    14.02\n",
       "                ],\n",
       "                [\n",
       "                    14.59,\n",
       "                    14.63,\n",
       "                    14.89,\n",
       "                    14.32\n",
       "                ],\n",
       "                [\n",
       "                    14.81,\n",
       "                    14.77,\n",
       "                    14.87,\n",
       "                    14.51\n",
       "                ],\n",
       "                [\n",
       "                    14.6,\n",
       "                    14.62,\n",
       "                    14.69,\n",
       "                    14.41\n",
       "                ]\n",
       "            ],\n",
       "            \"itemStyle\": {\n",
       "                \"color\": \"pink\",\n",
       "                \"color0\": \"black\"\n",
       "            }\n",
       "        }\n",
       "    ],\n",
       "    \"legend\": [\n",
       "        {\n",
       "            \"data\": [\n",
       "                \"kline\"\n",
       "            ],\n",
       "            \"selected\": {\n",
       "                \"kline\": true\n",
       "            },\n",
       "            \"show\": true,\n",
       "            \"padding\": 5,\n",
       "            \"itemGap\": 10,\n",
       "            \"itemWidth\": 25,\n",
       "            \"itemHeight\": 14\n",
       "        }\n",
       "    ],\n",
       "    \"tooltip\": {\n",
       "        \"show\": true,\n",
       "        \"trigger\": \"item\",\n",
       "        \"triggerOn\": \"mousemove|click\",\n",
       "        \"axisPointer\": {\n",
       "            \"type\": \"line\"\n",
       "        },\n",
       "        \"showContent\": true,\n",
       "        \"alwaysShowContent\": false,\n",
       "        \"showDelay\": 0,\n",
       "        \"hideDelay\": 100,\n",
       "        \"textStyle\": {\n",
       "            \"fontSize\": 14\n",
       "        },\n",
       "        \"borderWidth\": 0,\n",
       "        \"padding\": 5\n",
       "    },\n",
       "    \"xAxis\": [\n",
       "        {\n",
       "            \"show\": true,\n",
       "            \"scale\": true,\n",
       "            \"nameLocation\": \"end\",\n",
       "            \"nameGap\": 15,\n",
       "            \"gridIndex\": 0,\n",
       "            \"inverse\": false,\n",
       "            \"offset\": 0,\n",
       "            \"splitNumber\": 5,\n",
       "            \"minInterval\": 0,\n",
       "            \"splitLine\": {\n",
       "                \"show\": false,\n",
       "                \"lineStyle\": {\n",
       "                    \"show\": true,\n",
       "                    \"width\": 1,\n",
       "                    \"opacity\": 1,\n",
       "                    \"curveness\": 0,\n",
       "                    \"type\": \"solid\"\n",
       "                }\n",
       "            },\n",
       "            \"data\": [\n",
       "                \"2020-01-09\",\n",
       "                \"2020-01-10\",\n",
       "                \"2020-01-13\",\n",
       "                \"2020-01-14\",\n",
       "                \"2020-01-15\",\n",
       "                \"2020-01-16\",\n",
       "                \"2020-01-17\",\n",
       "                \"2020-01-20\",\n",
       "                \"2020-01-21\",\n",
       "                \"2020-01-22\",\n",
       "                \"2020-01-23\",\n",
       "                \"2020-02-03\",\n",
       "                \"2020-02-04\",\n",
       "                \"2020-02-05\",\n",
       "                \"2020-02-06\",\n",
       "                \"2020-02-07\"\n",
       "            ]\n",
       "        }\n",
       "    ],\n",
       "    \"yAxis\": [\n",
       "        {\n",
       "            \"show\": true,\n",
       "            \"scale\": true,\n",
       "            \"nameLocation\": \"end\",\n",
       "            \"nameGap\": 15,\n",
       "            \"gridIndex\": 0,\n",
       "            \"inverse\": false,\n",
       "            \"offset\": 0,\n",
       "            \"splitNumber\": 5,\n",
       "            \"minInterval\": 0,\n",
       "            \"splitLine\": {\n",
       "                \"show\": false,\n",
       "                \"lineStyle\": {\n",
       "                    \"show\": true,\n",
       "                    \"width\": 1,\n",
       "                    \"opacity\": 1,\n",
       "                    \"curveness\": 0,\n",
       "                    \"type\": \"solid\"\n",
       "                }\n",
       "            },\n",
       "            \"splitArea\": {\n",
       "                \"show\": true,\n",
       "                \"areaStyle\": {\n",
       "                    \"opacity\": 1\n",
       "                }\n",
       "            }\n",
       "        }\n",
       "    ],\n",
       "    \"title\": [\n",
       "        {\n",
       "            \"text\": \"Kline-\\u57fa\\u672c\\u793a\\u4f8b\",\n",
       "            \"padding\": 5,\n",
       "            \"itemGap\": 10\n",
       "        }\n",
       "    ],\n",
       "    \"dataZoom\": [\n",
       "        {\n",
       "            \"show\": true,\n",
       "            \"type\": \"inside\",\n",
       "            \"realtime\": true,\n",
       "            \"start\": 20,\n",
       "            \"end\": 80,\n",
       "            \"orient\": \"horizontal\",\n",
       "            \"zoomLock\": false,\n",
       "            \"filterMode\": \"filter\"\n",
       "        },\n",
       "        {\n",
       "            \"show\": true,\n",
       "            \"type\": \"slider\",\n",
       "            \"realtime\": true,\n",
       "            \"start\": 20,\n",
       "            \"end\": 80,\n",
       "            \"orient\": \"horizontal\",\n",
       "            \"zoomLock\": false,\n",
       "            \"filterMode\": \"filter\"\n",
       "        }\n",
       "    ]\n",
       "};\n",
       "                chart_cbf5d8c7dd0c4577916bf2b7aa849a0d.setOption(option_cbf5d8c7dd0c4577916bf2b7aa849a0d);\n",
       "        });\n",
       "    </script>\n"
      ],
      "text/plain": [
       "<pyecharts.render.display.HTML at 0x25376b2dfd0>"
      ]
     },
     "execution_count": 76,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "k1=Kline()\n",
    "k1.add_xaxis(data1.index.tolist())\n",
    "k1.add_yaxis(\"kline\", data1.values.tolist(),itemstyle_opts=opts.ItemStyleOpts(color=\"pink\", color0=\"black\"),)\n",
    "k1.set_global_opts(\n",
    "        yaxis_opts=opts.AxisOpts(is_scale=True,splitarea_opts=opts.SplitAreaOpts(areastyle_opts=opts.AreaStyleOpts(opacity=1)\n",
    "            )),\n",
    "        xaxis_opts=opts.AxisOpts(is_scale=True),\n",
    "        title_opts=opts.TitleOpts(title=\"Kline-基本示例\"),datazoom_opts=[opts.DataZoomOpts(type_=\"inside\"),opts.DataZoomOpts(type_=\"slider\")]\n",
    "    )\n",
    "k1.render_notebook()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## classwork3\n",
    "\n",
    "* 请做出中国联通的2019-01-01到当前的k线图\n",
    "\n",
    "* 请自行修改对应参数了解参数的作用\n",
    "\n",
    "* 能否自己通过学习pyechart的官网例子做出每天的最高价的曲线图\n",
    "https://gallery.pyecharts.org/#/Line/README"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 股票中的均线\n",
    "\n",
    "* talib\n",
    "\n",
    "TA-Lib，全称“Technical Analysis Library”, 即技术分析库，是Python金融量化的高级库，涵盖了150多种股票、期货交易软件中常用的技术分析指标，如MACD、RSI、KDJ、动量指标、布林带等等。TA-Lib可分为10个子板块：Overlap Studies(重叠指标)，Momentum Indicators(动量指标)，Volume Indicators(交易量指标)，Cycle Indicators(周期指标)，Price Transform(价格变换)，Volatility Indicators(波动率指标)，Pattern Recognition(模式识别)，Statistic Functions(统计函数)，Math Transform(数学变换)和Math Operators(数学运算)，\n",
    "\n",
    "链接：https://www.jianshu.com/p/7ecc7962d638\n",
    "\n",
    "TA-LIB 200多个技术指标含有及计算式:\n",
    "\n",
    "https://blog.csdn.net/MARY197011111/article/details/79622184\n",
    "\n",
    "重叠指标\n",
    "\n",
    "https://www.jianshu.com/p/7ecc7962d638\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "* 简单作图"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [],
   "source": [
    "import talib"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [],
   "source": [
    "data1=stock_pinan.loc[\"2020-01-09\":\"2022-02-07\",[\"开盘\",\"收盘\",\"最高\",\"最低\"]]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "日期\n",
       "2020-01-09    16.79\n",
       "2020-01-10    16.69\n",
       "2020-01-13    16.99\n",
       "2020-01-14    16.76\n",
       "2020-01-15    16.52\n",
       "              ...  \n",
       "2022-01-25    16.85\n",
       "2022-01-26    16.65\n",
       "2022-01-27    16.30\n",
       "2022-01-28    15.83\n",
       "2022-02-07    16.39\n",
       "Name: 收盘, Length: 501, dtype: float64"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data1[\"收盘\"]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 93,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Help on function SMA in module talib._ta_lib:\n",
      "\n",
      "SMA(...)\n",
      "    SMA(real[, timeperiod=?])\n",
      "    \n",
      "    Simple Moving Average (Overlap Studies)\n",
      "    \n",
      "    Inputs:\n",
      "        real: (any ndarray)\n",
      "    Parameters:\n",
      "        timeperiod: 30\n",
      "    Outputs:\n",
      "        real\n",
      "\n"
     ]
    }
   ],
   "source": [
    "help(talib.SMA)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [],
   "source": [
    "y_SMA=talib.SMA(data1[\"收盘\"],10)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "日期\n",
       "2020-01-09     0.000\n",
       "2020-01-10     0.000\n",
       "2020-01-13     0.000\n",
       "2020-01-14     0.000\n",
       "2020-01-15     0.000\n",
       "               ...  \n",
       "2022-01-25    16.828\n",
       "2022-01-26    16.793\n",
       "2022-01-27    16.725\n",
       "2022-01-28    16.675\n",
       "2022-02-07    16.692\n",
       "Length: 501, dtype: float64"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "y_SMA.fillna(0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 118,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:xlabel='日期'>"
      ]
     },
     "execution_count": 118,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "y_SMA.plot(rot=30)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 119,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "日期\n",
       "2020-01-09       NaN\n",
       "2020-01-10       NaN\n",
       "2020-01-13       NaN\n",
       "2020-01-14       NaN\n",
       "2020-01-15       NaN\n",
       "               ...  \n",
       "2022-01-25    16.828\n",
       "2022-01-26    16.793\n",
       "2022-01-27    16.725\n",
       "2022-01-28    16.675\n",
       "2022-02-07    16.692\n",
       "Name: 收盘, Length: 501, dtype: float64"
      ]
     },
     "execution_count": 119,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data1[\"收盘\"].rolling(10).mean()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 123,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:xlabel='日期'>"
      ]
     },
     "execution_count": 123,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1296x360 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "data1[\"收盘\"].rolling(5).mean().plot(figsize=(18,5))\n",
    "data1[\"收盘\"].rolling(10).mean().plot()\n",
    "data1[\"收盘\"].rolling(20).mean().plot()\n",
    "data1[\"收盘\"].rolling(30).mean().plot()\n",
    "data1[\"收盘\"].plot(style=\"-o\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "* pyecharts可视化"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 111,
   "metadata": {},
   "outputs": [],
   "source": [
    "from pyecharts.charts import Line"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 125,
   "metadata": {},
   "outputs": [],
   "source": [
    "#y_SMA.index.tolist()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 126,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "\n",
       "<script>\n",
       "    require.config({\n",
       "        paths: {\n",
       "            'echarts':'https://assets.pyecharts.org/assets/echarts.min'\n",
       "        }\n",
       "    });\n",
       "</script>\n",
       "\n",
       "        <div id=\"984accb27d4c4bd393eac69d5f5f7fee\" style=\"width:900px; height:500px;\"></div>\n",
       "\n",
       "<script>\n",
       "        require(['echarts'], function(echarts) {\n",
       "                var chart_984accb27d4c4bd393eac69d5f5f7fee = echarts.init(\n",
       "                    document.getElementById('984accb27d4c4bd393eac69d5f5f7fee'), 'white', {renderer: 'canvas'});\n",
       "                var option_984accb27d4c4bd393eac69d5f5f7fee = {\n",
       "    \"animation\": true,\n",
       "    \"animationThreshold\": 2000,\n",
       "    \"animationDuration\": 1000,\n",
       "    \"animationEasing\": \"cubicOut\",\n",
       "    \"animationDelay\": 0,\n",
       "    \"animationDurationUpdate\": 300,\n",
       "    \"animationEasingUpdate\": \"cubicOut\",\n",
       "    \"animationDelayUpdate\": 0,\n",
       "    \"color\": [\n",
       "        \"#c23531\",\n",
       "        \"#2f4554\",\n",
       "        \"#61a0a8\",\n",
       "        \"#d48265\",\n",
       "        \"#749f83\",\n",
       "        \"#ca8622\",\n",
       "        \"#bda29a\",\n",
       "        \"#6e7074\",\n",
       "        \"#546570\",\n",
       "        \"#c4ccd3\",\n",
       "        \"#f05b72\",\n",
       "        \"#ef5b9c\",\n",
       "        \"#f47920\",\n",
       "        \"#905a3d\",\n",
       "        \"#fab27b\",\n",
       "        \"#2a5caa\",\n",
       "        \"#444693\",\n",
       "        \"#726930\",\n",
       "        \"#b2d235\",\n",
       "        \"#6d8346\",\n",
       "        \"#ac6767\",\n",
       "        \"#1d953f\",\n",
       "        \"#6950a1\",\n",
       "        \"#918597\"\n",
       "    ],\n",
       "    \"series\": [\n",
       "        {\n",
       "            \"type\": \"line\",\n",
       "            \"name\": \"MA10\",\n",
       "            \"connectNulls\": false,\n",
       "            \"symbolSize\": 4,\n",
       "            \"showSymbol\": true,\n",
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       "                \"2022-01-06\",\n",
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       "                \"2022-01-12\",\n",
       "                \"2022-01-13\",\n",
       "                \"2022-01-14\",\n",
       "                \"2022-01-17\",\n",
       "                \"2022-01-18\",\n",
       "                \"2022-01-19\",\n",
       "                \"2022-01-20\",\n",
       "                \"2022-01-21\",\n",
       "                \"2022-01-24\",\n",
       "                \"2022-01-25\",\n",
       "                \"2022-01-26\",\n",
       "                \"2022-01-27\",\n",
       "                \"2022-01-28\",\n",
       "                \"2022-02-07\"\n",
       "            ]\n",
       "        }\n",
       "    ],\n",
       "    \"yAxis\": [\n",
       "        {\n",
       "            \"show\": true,\n",
       "            \"scale\": false,\n",
       "            \"nameLocation\": \"end\",\n",
       "            \"nameGap\": 15,\n",
       "            \"gridIndex\": 0,\n",
       "            \"inverse\": false,\n",
       "            \"offset\": 0,\n",
       "            \"splitNumber\": 5,\n",
       "            \"minInterval\": 0,\n",
       "            \"splitLine\": {\n",
       "                \"show\": false,\n",
       "                \"lineStyle\": {\n",
       "                    \"show\": true,\n",
       "                    \"width\": 1,\n",
       "                    \"opacity\": 1,\n",
       "                    \"curveness\": 0,\n",
       "                    \"type\": \"solid\"\n",
       "                }\n",
       "            }\n",
       "        }\n",
       "    ]\n",
       "};\n",
       "                chart_984accb27d4c4bd393eac69d5f5f7fee.setOption(option_984accb27d4c4bd393eac69d5f5f7fee);\n",
       "        });\n",
       "    </script>\n"
      ],
      "text/plain": [
       "<pyecharts.render.display.HTML at 0x2537e775e50>"
      ]
     },
     "execution_count": 126,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "c1=Line()\n",
    "c1.add_xaxis(y_SMA.index.tolist())\n",
    "c1.add_yaxis(\"MA10\",y_SMA.values.tolist(),\n",
    "        linestyle_opts=opts.LineStyleOpts(opacity=0.5),\n",
    "        label_opts=opts.LabelOpts(is_show=False),\n",
    "    )\n",
    "c1.render_notebook()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 127,
   "metadata": {},
   "outputs": [],
   "source": [
    "y_SMA20=talib.SMA(data1[\"收盘\"],20)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 131,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "\n",
       "<script>\n",
       "    require.config({\n",
       "        paths: {\n",
       "            'echarts':'https://assets.pyecharts.org/assets/echarts.min'\n",
       "        }\n",
       "    });\n",
       "</script>\n",
       "\n",
       "        <div id=\"f3bc868fc8b8449f97f3698e3128680d\" style=\"width:900px; height:500px;\"></div>\n",
       "\n",
       "<script>\n",
       "        require(['echarts'], function(echarts) {\n",
       "                var chart_f3bc868fc8b8449f97f3698e3128680d = echarts.init(\n",
       "                    document.getElementById('f3bc868fc8b8449f97f3698e3128680d'), 'white', {renderer: 'canvas'});\n",
       "                var option_f3bc868fc8b8449f97f3698e3128680d = {\n",
       "    \"animation\": true,\n",
       "    \"animationThreshold\": 2000,\n",
       "    \"animationDuration\": 1000,\n",
       "    \"animationEasing\": \"cubicOut\",\n",
       "    \"animationDelay\": 0,\n",
       "    \"animationDurationUpdate\": 300,\n",
       "    \"animationEasingUpdate\": \"cubicOut\",\n",
       "    \"animationDelayUpdate\": 0,\n",
       "    \"color\": [\n",
       "        \"#c23531\",\n",
       "        \"#2f4554\",\n",
       "        \"#61a0a8\",\n",
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       "        \"#6e7074\",\n",
       "        \"#546570\",\n",
       "        \"#c4ccd3\",\n",
       "        \"#f05b72\",\n",
       "        \"#ef5b9c\",\n",
       "        \"#f47920\",\n",
       "        \"#905a3d\",\n",
       "        \"#fab27b\",\n",
       "        \"#2a5caa\",\n",
       "        \"#444693\",\n",
       "        \"#726930\",\n",
       "        \"#b2d235\",\n",
       "        \"#6d8346\",\n",
       "        \"#ac6767\",\n",
       "        \"#1d953f\",\n",
       "        \"#6950a1\",\n",
       "        \"#918597\"\n",
       "    ],\n",
       "    \"series\": [\n",
       "        {\n",
       "            \"type\": \"line\",\n",
       "            \"name\": \"MA20\",\n",
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       "                \"2021-08-30\",\n",
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       "                \"2021-09-02\",\n",
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       "                \"2021-09-13\",\n",
       "                \"2021-09-14\",\n",
       "                \"2021-09-15\",\n",
       "                \"2021-09-16\",\n",
       "                \"2021-09-17\",\n",
       "                \"2021-09-22\",\n",
       "                \"2021-09-23\",\n",
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       "                \"2021-10-13\",\n",
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       "                \"2021-10-15\",\n",
       "                \"2021-10-18\",\n",
       "                \"2021-10-19\",\n",
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       "                \"2021-10-22\",\n",
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       "                \"2021-11-02\",\n",
       "                \"2021-11-03\",\n",
       "                \"2021-11-04\",\n",
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       "                \"2021-11-08\",\n",
       "                \"2021-11-09\",\n",
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       "                \"2021-11-12\",\n",
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       "                \"2021-11-16\",\n",
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       "                \"2021-11-18\",\n",
       "                \"2021-11-19\",\n",
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       "                \"2021-11-24\",\n",
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       "                \"2021-11-30\",\n",
       "                \"2021-12-01\",\n",
       "                \"2021-12-02\",\n",
       "                \"2021-12-03\",\n",
       "                \"2021-12-06\",\n",
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       "                \"2021-12-09\",\n",
       "                \"2021-12-10\",\n",
       "                \"2021-12-13\",\n",
       "                \"2021-12-14\",\n",
       "                \"2021-12-15\",\n",
       "                \"2021-12-16\",\n",
       "                \"2021-12-17\",\n",
       "                \"2021-12-20\",\n",
       "                \"2021-12-21\",\n",
       "                \"2021-12-22\",\n",
       "                \"2021-12-23\",\n",
       "                \"2021-12-24\",\n",
       "                \"2021-12-27\",\n",
       "                \"2021-12-28\",\n",
       "                \"2021-12-29\",\n",
       "                \"2021-12-30\",\n",
       "                \"2021-12-31\",\n",
       "                \"2022-01-04\",\n",
       "                \"2022-01-05\",\n",
       "                \"2022-01-06\",\n",
       "                \"2022-01-07\",\n",
       "                \"2022-01-10\",\n",
       "                \"2022-01-11\",\n",
       "                \"2022-01-12\",\n",
       "                \"2022-01-13\",\n",
       "                \"2022-01-14\",\n",
       "                \"2022-01-17\",\n",
       "                \"2022-01-18\",\n",
       "                \"2022-01-19\",\n",
       "                \"2022-01-20\",\n",
       "                \"2022-01-21\",\n",
       "                \"2022-01-24\",\n",
       "                \"2022-01-25\",\n",
       "                \"2022-01-26\",\n",
       "                \"2022-01-27\",\n",
       "                \"2022-01-28\",\n",
       "                \"2022-02-07\"\n",
       "            ]\n",
       "        }\n",
       "    ],\n",
       "    \"yAxis\": [\n",
       "        {\n",
       "            \"show\": true,\n",
       "            \"scale\": false,\n",
       "            \"nameLocation\": \"end\",\n",
       "            \"nameGap\": 15,\n",
       "            \"gridIndex\": 0,\n",
       "            \"inverse\": false,\n",
       "            \"offset\": 0,\n",
       "            \"splitNumber\": 5,\n",
       "            \"minInterval\": 0,\n",
       "            \"splitLine\": {\n",
       "                \"show\": false,\n",
       "                \"lineStyle\": {\n",
       "                    \"show\": true,\n",
       "                    \"width\": 1,\n",
       "                    \"opacity\": 1,\n",
       "                    \"curveness\": 0,\n",
       "                    \"type\": \"solid\"\n",
       "                }\n",
       "            }\n",
       "        }\n",
       "    ]\n",
       "};\n",
       "                chart_f3bc868fc8b8449f97f3698e3128680d.setOption(option_f3bc868fc8b8449f97f3698e3128680d);\n",
       "        });\n",
       "    </script>\n"
      ],
      "text/plain": [
       "<pyecharts.render.display.HTML at 0x2537e5a75e0>"
      ]
     },
     "execution_count": 131,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "c3=Line()\n",
    "c3.add_xaxis(y_SMA20.index.tolist())\n",
    "c3.add_yaxis(\"MA20\",y_SMA20.values.tolist(),\n",
    "        linestyle_opts=opts.LineStyleOpts(opacity=0.5),\n",
    "        label_opts=opts.LabelOpts(is_show=False),\n",
    "    )\n",
    "c3.render_notebook()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 132,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "\n",
       "<script>\n",
       "    require.config({\n",
       "        paths: {\n",
       "            'echarts':'https://assets.pyecharts.org/assets/echarts.min'\n",
       "        }\n",
       "    });\n",
       "</script>\n",
       "\n",
       "        <div id=\"ec9d9b6a8d3a42318f7e52f7719545fa\" style=\"width:900px; height:500px;\"></div>\n",
       "\n",
       "<script>\n",
       "        require(['echarts'], function(echarts) {\n",
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       "                var option_ec9d9b6a8d3a42318f7e52f7719545fa = {\n",
       "    \"animation\": true,\n",
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       "        \"#ac6767\",\n",
       "        \"#1d953f\",\n",
       "        \"#6950a1\",\n",
       "        \"#918597\"\n",
       "    ],\n",
       "    \"series\": [\n",
       "        {\n",
       "            \"type\": \"candlestick\",\n",
       "            \"name\": \"kline\",\n",
       "            \"data\": [\n",
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       "                \"2020-07-22\",\n",
       "                \"2020-07-23\",\n",
       "                \"2020-07-24\",\n",
       "                \"2020-07-27\",\n",
       "                \"2020-07-28\",\n",
       "                \"2020-07-29\",\n",
       "                \"2020-07-30\",\n",
       "                \"2020-07-31\",\n",
       "                \"2020-08-03\",\n",
       "                \"2020-08-04\",\n",
       "                \"2020-08-05\",\n",
       "                \"2020-08-06\",\n",
       "                \"2020-08-07\",\n",
       "                \"2020-08-10\",\n",
       "                \"2020-08-11\",\n",
       "                \"2020-08-12\",\n",
       "                \"2020-08-13\",\n",
       "                \"2020-08-14\",\n",
       "                \"2020-08-17\",\n",
       "                \"2020-08-18\",\n",
       "                \"2020-08-19\",\n",
       "                \"2020-08-20\",\n",
       "                \"2020-08-21\",\n",
       "                \"2020-08-24\",\n",
       "                \"2020-08-25\",\n",
       "                \"2020-08-26\",\n",
       "                \"2020-08-27\",\n",
       "                \"2020-08-28\",\n",
       "                \"2020-08-31\",\n",
       "                \"2020-09-01\",\n",
       "                \"2020-09-02\",\n",
       "                \"2020-09-03\",\n",
       "                \"2020-09-04\",\n",
       "                \"2020-09-07\",\n",
       "                \"2020-09-08\",\n",
       "                \"2020-09-09\",\n",
       "                \"2020-09-10\",\n",
       "                \"2020-09-11\",\n",
       "                \"2020-09-14\",\n",
       "                \"2020-09-15\",\n",
       "                \"2020-09-16\",\n",
       "                \"2020-09-17\",\n",
       "                \"2020-09-18\",\n",
       "                \"2020-09-21\",\n",
       "                \"2020-09-22\",\n",
       "                \"2020-09-23\",\n",
       "                \"2020-09-24\",\n",
       "                \"2020-09-25\",\n",
       "                \"2020-09-28\",\n",
       "                \"2020-09-29\",\n",
       "                \"2020-09-30\",\n",
       "                \"2020-10-09\",\n",
       "                \"2020-10-12\",\n",
       "                \"2020-10-13\",\n",
       "                \"2020-10-14\",\n",
       "                \"2020-10-15\",\n",
       "                \"2020-10-16\",\n",
       "                \"2020-10-19\",\n",
       "                \"2020-10-20\",\n",
       "                \"2020-10-21\",\n",
       "                \"2020-10-22\",\n",
       "                \"2020-10-23\",\n",
       "                \"2020-10-26\",\n",
       "                \"2020-10-27\",\n",
       "                \"2020-10-28\",\n",
       "                \"2020-10-29\",\n",
       "                \"2020-10-30\",\n",
       "                \"2020-11-02\",\n",
       "                \"2020-11-03\",\n",
       "                \"2020-11-04\",\n",
       "                \"2020-11-05\",\n",
       "                \"2020-11-06\",\n",
       "                \"2020-11-09\",\n",
       "                \"2020-11-10\",\n",
       "                \"2020-11-11\",\n",
       "                \"2020-11-12\",\n",
       "                \"2020-11-13\",\n",
       "                \"2020-11-16\",\n",
       "                \"2020-11-17\",\n",
       "                \"2020-11-18\",\n",
       "                \"2020-11-19\",\n",
       "                \"2020-11-20\",\n",
       "                \"2020-11-23\",\n",
       "                \"2020-11-24\",\n",
       "                \"2020-11-25\",\n",
       "                \"2020-11-26\",\n",
       "                \"2020-11-27\",\n",
       "                \"2020-11-30\",\n",
       "                \"2020-12-01\",\n",
       "                \"2020-12-02\",\n",
       "                \"2020-12-03\",\n",
       "                \"2020-12-04\",\n",
       "                \"2020-12-07\",\n",
       "                \"2020-12-08\",\n",
       "                \"2020-12-09\",\n",
       "                \"2020-12-10\",\n",
       "                \"2020-12-11\",\n",
       "                \"2020-12-14\",\n",
       "                \"2020-12-15\",\n",
       "                \"2020-12-16\",\n",
       "                \"2020-12-17\",\n",
       "                \"2020-12-18\",\n",
       "                \"2020-12-21\",\n",
       "                \"2020-12-22\",\n",
       "                \"2020-12-23\",\n",
       "                \"2020-12-24\",\n",
       "                \"2020-12-25\",\n",
       "                \"2020-12-28\",\n",
       "                \"2020-12-29\",\n",
       "                \"2020-12-30\",\n",
       "                \"2020-12-31\",\n",
       "                \"2021-01-04\",\n",
       "                \"2021-01-05\",\n",
       "                \"2021-01-06\",\n",
       "                \"2021-01-07\",\n",
       "                \"2021-01-08\",\n",
       "                \"2021-01-11\",\n",
       "                \"2021-01-12\",\n",
       "                \"2021-01-13\",\n",
       "                \"2021-01-14\",\n",
       "                \"2021-01-15\",\n",
       "                \"2021-01-18\",\n",
       "                \"2021-01-19\",\n",
       "                \"2021-01-20\",\n",
       "                \"2021-01-21\",\n",
       "                \"2021-01-22\",\n",
       "                \"2021-01-25\",\n",
       "                \"2021-01-26\",\n",
       "                \"2021-01-27\",\n",
       "                \"2021-01-28\",\n",
       "                \"2021-01-29\",\n",
       "                \"2021-02-01\",\n",
       "                \"2021-02-02\",\n",
       "                \"2021-02-03\",\n",
       "                \"2021-02-04\",\n",
       "                \"2021-02-05\",\n",
       "                \"2021-02-08\",\n",
       "                \"2021-02-09\",\n",
       "                \"2021-02-10\",\n",
       "                \"2021-02-18\",\n",
       "                \"2021-02-19\",\n",
       "                \"2021-02-22\",\n",
       "                \"2021-02-23\",\n",
       "                \"2021-02-24\",\n",
       "                \"2021-02-25\",\n",
       "                \"2021-02-26\",\n",
       "                \"2021-03-01\",\n",
       "                \"2021-03-02\",\n",
       "                \"2021-03-03\",\n",
       "                \"2021-03-04\",\n",
       "                \"2021-03-05\",\n",
       "                \"2021-03-08\",\n",
       "                \"2021-03-09\",\n",
       "                \"2021-03-10\",\n",
       "                \"2021-03-11\",\n",
       "                \"2021-03-12\",\n",
       "                \"2021-03-15\",\n",
       "                \"2021-03-16\",\n",
       "                \"2021-03-17\",\n",
       "                \"2021-03-18\",\n",
       "                \"2021-03-19\",\n",
       "                \"2021-03-22\",\n",
       "                \"2021-03-23\",\n",
       "                \"2021-03-24\",\n",
       "                \"2021-03-25\",\n",
       "                \"2021-03-26\",\n",
       "                \"2021-03-29\",\n",
       "                \"2021-03-30\",\n",
       "                \"2021-03-31\",\n",
       "                \"2021-04-01\",\n",
       "                \"2021-04-02\",\n",
       "                \"2021-04-06\",\n",
       "                \"2021-04-07\",\n",
       "                \"2021-04-08\",\n",
       "                \"2021-04-09\",\n",
       "                \"2021-04-12\",\n",
       "                \"2021-04-13\",\n",
       "                \"2021-04-14\",\n",
       "                \"2021-04-15\",\n",
       "                \"2021-04-16\",\n",
       "                \"2021-04-19\",\n",
       "                \"2021-04-20\",\n",
       "                \"2021-04-21\",\n",
       "                \"2021-04-22\",\n",
       "                \"2021-04-23\",\n",
       "                \"2021-04-26\",\n",
       "                \"2021-04-27\",\n",
       "                \"2021-04-28\",\n",
       "                \"2021-04-29\",\n",
       "                \"2021-04-30\",\n",
       "                \"2021-05-06\",\n",
       "                \"2021-05-07\",\n",
       "                \"2021-05-10\",\n",
       "                \"2021-05-11\",\n",
       "                \"2021-05-12\",\n",
       "                \"2021-05-13\",\n",
       "                \"2021-05-14\",\n",
       "                \"2021-05-17\",\n",
       "                \"2021-05-18\",\n",
       "                \"2021-05-19\",\n",
       "                \"2021-05-20\",\n",
       "                \"2021-05-21\",\n",
       "                \"2021-05-24\",\n",
       "                \"2021-05-25\",\n",
       "                \"2021-05-26\",\n",
       "                \"2021-05-27\",\n",
       "                \"2021-05-28\",\n",
       "                \"2021-05-31\",\n",
       "                \"2021-06-01\",\n",
       "                \"2021-06-02\",\n",
       "                \"2021-06-03\",\n",
       "                \"2021-06-04\",\n",
       "                \"2021-06-07\",\n",
       "                \"2021-06-08\",\n",
       "                \"2021-06-09\",\n",
       "                \"2021-06-10\",\n",
       "                \"2021-06-11\",\n",
       "                \"2021-06-15\",\n",
       "                \"2021-06-16\",\n",
       "                \"2021-06-17\",\n",
       "                \"2021-06-18\",\n",
       "                \"2021-06-21\",\n",
       "                \"2021-06-22\",\n",
       "                \"2021-06-23\",\n",
       "                \"2021-06-24\",\n",
       "                \"2021-06-25\",\n",
       "                \"2021-06-28\",\n",
       "                \"2021-06-29\",\n",
       "                \"2021-06-30\",\n",
       "                \"2021-07-01\",\n",
       "                \"2021-07-02\",\n",
       "                \"2021-07-05\",\n",
       "                \"2021-07-06\",\n",
       "                \"2021-07-07\",\n",
       "                \"2021-07-08\",\n",
       "                \"2021-07-09\",\n",
       "                \"2021-07-12\",\n",
       "                \"2021-07-13\",\n",
       "                \"2021-07-14\",\n",
       "                \"2021-07-15\",\n",
       "                \"2021-07-16\",\n",
       "                \"2021-07-19\",\n",
       "                \"2021-07-20\",\n",
       "                \"2021-07-21\",\n",
       "                \"2021-07-22\",\n",
       "                \"2021-07-23\",\n",
       "                \"2021-07-26\",\n",
       "                \"2021-07-27\",\n",
       "                \"2021-07-28\",\n",
       "                \"2021-07-29\",\n",
       "                \"2021-07-30\",\n",
       "                \"2021-08-02\",\n",
       "                \"2021-08-03\",\n",
       "                \"2021-08-04\",\n",
       "                \"2021-08-05\",\n",
       "                \"2021-08-06\",\n",
       "                \"2021-08-09\",\n",
       "                \"2021-08-10\",\n",
       "                \"2021-08-11\",\n",
       "                \"2021-08-12\",\n",
       "                \"2021-08-13\",\n",
       "                \"2021-08-16\",\n",
       "                \"2021-08-17\",\n",
       "                \"2021-08-18\",\n",
       "                \"2021-08-19\",\n",
       "                \"2021-08-20\",\n",
       "                \"2021-08-23\",\n",
       "                \"2021-08-24\",\n",
       "                \"2021-08-25\",\n",
       "                \"2021-08-26\",\n",
       "                \"2021-08-27\",\n",
       "                \"2021-08-30\",\n",
       "                \"2021-08-31\",\n",
       "                \"2021-09-01\",\n",
       "                \"2021-09-02\",\n",
       "                \"2021-09-03\",\n",
       "                \"2021-09-06\",\n",
       "                \"2021-09-07\",\n",
       "                \"2021-09-08\",\n",
       "                \"2021-09-09\",\n",
       "                \"2021-09-10\",\n",
       "                \"2021-09-13\",\n",
       "                \"2021-09-14\",\n",
       "                \"2021-09-15\",\n",
       "                \"2021-09-16\",\n",
       "                \"2021-09-17\",\n",
       "                \"2021-09-22\",\n",
       "                \"2021-09-23\",\n",
       "                \"2021-09-24\",\n",
       "                \"2021-09-27\",\n",
       "                \"2021-09-28\",\n",
       "                \"2021-09-29\",\n",
       "                \"2021-09-30\",\n",
       "                \"2021-10-08\",\n",
       "                \"2021-10-11\",\n",
       "                \"2021-10-12\",\n",
       "                \"2021-10-13\",\n",
       "                \"2021-10-14\",\n",
       "                \"2021-10-15\",\n",
       "                \"2021-10-18\",\n",
       "                \"2021-10-19\",\n",
       "                \"2021-10-20\",\n",
       "                \"2021-10-21\",\n",
       "                \"2021-10-22\",\n",
       "                \"2021-10-25\",\n",
       "                \"2021-10-26\",\n",
       "                \"2021-10-27\",\n",
       "                \"2021-10-28\",\n",
       "                \"2021-10-29\",\n",
       "                \"2021-11-01\",\n",
       "                \"2021-11-02\",\n",
       "                \"2021-11-03\",\n",
       "                \"2021-11-04\",\n",
       "                \"2021-11-05\",\n",
       "                \"2021-11-08\",\n",
       "                \"2021-11-09\",\n",
       "                \"2021-11-10\",\n",
       "                \"2021-11-11\",\n",
       "                \"2021-11-12\",\n",
       "                \"2021-11-15\",\n",
       "                \"2021-11-16\",\n",
       "                \"2021-11-17\",\n",
       "                \"2021-11-18\",\n",
       "                \"2021-11-19\",\n",
       "                \"2021-11-22\",\n",
       "                \"2021-11-23\",\n",
       "                \"2021-11-24\",\n",
       "                \"2021-11-25\",\n",
       "                \"2021-11-26\",\n",
       "                \"2021-11-29\",\n",
       "                \"2021-11-30\",\n",
       "                \"2021-12-01\",\n",
       "                \"2021-12-02\",\n",
       "                \"2021-12-03\",\n",
       "                \"2021-12-06\",\n",
       "                \"2021-12-07\",\n",
       "                \"2021-12-08\",\n",
       "                \"2021-12-09\",\n",
       "                \"2021-12-10\",\n",
       "                \"2021-12-13\",\n",
       "                \"2021-12-14\",\n",
       "                \"2021-12-15\",\n",
       "                \"2021-12-16\",\n",
       "                \"2021-12-17\",\n",
       "                \"2021-12-20\",\n",
       "                \"2021-12-21\",\n",
       "                \"2021-12-22\",\n",
       "                \"2021-12-23\",\n",
       "                \"2021-12-24\",\n",
       "                \"2021-12-27\",\n",
       "                \"2021-12-28\",\n",
       "                \"2021-12-29\",\n",
       "                \"2021-12-30\",\n",
       "                \"2021-12-31\",\n",
       "                \"2022-01-04\",\n",
       "                \"2022-01-05\",\n",
       "                \"2022-01-06\",\n",
       "                \"2022-01-07\",\n",
       "                \"2022-01-10\",\n",
       "                \"2022-01-11\",\n",
       "                \"2022-01-12\",\n",
       "                \"2022-01-13\",\n",
       "                \"2022-01-14\",\n",
       "                \"2022-01-17\",\n",
       "                \"2022-01-18\",\n",
       "                \"2022-01-19\",\n",
       "                \"2022-01-20\",\n",
       "                \"2022-01-21\",\n",
       "                \"2022-01-24\",\n",
       "                \"2022-01-25\",\n",
       "                \"2022-01-26\",\n",
       "                \"2022-01-27\",\n",
       "                \"2022-01-28\",\n",
       "                \"2022-02-07\"\n",
       "            ]\n",
       "        }\n",
       "    ],\n",
       "    \"yAxis\": [\n",
       "        {\n",
       "            \"show\": true,\n",
       "            \"scale\": true,\n",
       "            \"nameLocation\": \"end\",\n",
       "            \"nameGap\": 15,\n",
       "            \"gridIndex\": 0,\n",
       "            \"inverse\": false,\n",
       "            \"offset\": 0,\n",
       "            \"splitNumber\": 5,\n",
       "            \"minInterval\": 0,\n",
       "            \"splitLine\": {\n",
       "                \"show\": false,\n",
       "                \"lineStyle\": {\n",
       "                    \"show\": true,\n",
       "                    \"width\": 1,\n",
       "                    \"opacity\": 1,\n",
       "                    \"curveness\": 0,\n",
       "                    \"type\": \"solid\"\n",
       "                }\n",
       "            },\n",
       "            \"splitArea\": {\n",
       "                \"show\": true,\n",
       "                \"areaStyle\": {\n",
       "                    \"opacity\": 1\n",
       "                }\n",
       "            }\n",
       "        }\n",
       "    ],\n",
       "    \"title\": [\n",
       "        {\n",
       "            \"text\": \"Kline-\\u57fa\\u672c\\u793a\\u4f8b\",\n",
       "            \"padding\": 5,\n",
       "            \"itemGap\": 10\n",
       "        }\n",
       "    ],\n",
       "    \"dataZoom\": [\n",
       "        {\n",
       "            \"show\": true,\n",
       "            \"type\": \"inside\",\n",
       "            \"realtime\": true,\n",
       "            \"start\": 20,\n",
       "            \"end\": 80,\n",
       "            \"orient\": \"horizontal\",\n",
       "            \"zoomLock\": false,\n",
       "            \"filterMode\": \"filter\"\n",
       "        },\n",
       "        {\n",
       "            \"show\": true,\n",
       "            \"type\": \"slider\",\n",
       "            \"realtime\": true,\n",
       "            \"start\": 20,\n",
       "            \"end\": 80,\n",
       "            \"orient\": \"horizontal\",\n",
       "            \"zoomLock\": false,\n",
       "            \"filterMode\": \"filter\"\n",
       "        }\n",
       "    ]\n",
       "};\n",
       "                chart_ec9d9b6a8d3a42318f7e52f7719545fa.setOption(option_ec9d9b6a8d3a42318f7e52f7719545fa);\n",
       "        });\n",
       "    </script>\n"
      ],
      "text/plain": [
       "<pyecharts.render.display.HTML at 0x2537e5b1310>"
      ]
     },
     "execution_count": 132,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "c=Kline()\n",
    "c.add_xaxis(data1.index.tolist())\n",
    "c.add_yaxis(\"kline\", data1.values.tolist(),itemstyle_opts=opts.ItemStyleOpts(color=\"pink\", color0=\"black\"),)\n",
    "c.set_global_opts(\n",
    "        yaxis_opts=opts.AxisOpts(is_scale=True,splitarea_opts=opts.SplitAreaOpts(areastyle_opts=opts.AreaStyleOpts(opacity=1)\n",
    "            )),\n",
    "        xaxis_opts=opts.AxisOpts(is_scale=True),\n",
    "        title_opts=opts.TitleOpts(title=\"Kline-基本示例\"),datazoom_opts=[opts.DataZoomOpts(type_=\"inside\"),opts.DataZoomOpts(type_=\"slider\")]\n",
    "    )\n",
    "c.render_notebook()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 133,
   "metadata": {},
   "outputs": [],
   "source": [
    "c2=c.overlap(c1)\n",
    "c4=c2.overlap(c3)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 134,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "\n",
       "<script>\n",
       "    require.config({\n",
       "        paths: {\n",
       "            'echarts':'https://assets.pyecharts.org/assets/echarts.min'\n",
       "        }\n",
       "    });\n",
       "</script>\n",
       "\n",
       "        <div id=\"64f27d34de7d410db64ac4f0584b032a\" style=\"width:900px; height:500px;\"></div>\n",
       "\n",
       "<script>\n",
       "        require(['echarts'], function(echarts) {\n",
       "                var chart_64f27d34de7d410db64ac4f0584b032a = echarts.init(\n",
       "                    document.getElementById('64f27d34de7d410db64ac4f0584b032a'), 'white', {renderer: 'canvas'});\n",
       "                var option_64f27d34de7d410db64ac4f0584b032a = {\n",
       "    \"animation\": true,\n",
       "    \"animationThreshold\": 2000,\n",
       "    \"animationDuration\": 1000,\n",
       "    \"animationEasing\": \"cubicOut\",\n",
       "    \"animationDelay\": 0,\n",
       "    \"animationDurationUpdate\": 300,\n",
       "    \"animationEasingUpdate\": \"cubicOut\",\n",
       "    \"animationDelayUpdate\": 0,\n",
       "    \"color\": [\n",
       "        \"#c23531\",\n",
       "        \"#2f4554\",\n",
       "        \"#61a0a8\",\n",
       "        \"#d48265\",\n",
       "        \"#749f83\",\n",
       "        \"#ca8622\",\n",
       "        \"#bda29a\",\n",
       "        \"#6e7074\",\n",
       "        \"#546570\",\n",
       "        \"#c4ccd3\",\n",
       "        \"#f05b72\",\n",
       "        \"#ef5b9c\",\n",
       "        \"#f47920\",\n",
       "        \"#905a3d\",\n",
       "        \"#fab27b\",\n",
       "        \"#2a5caa\",\n",
       "        \"#444693\",\n",
       "        \"#726930\",\n",
       "        \"#b2d235\",\n",
       "        \"#6d8346\",\n",
       "        \"#ac6767\",\n",
       "        \"#1d953f\",\n",
       "        \"#6950a1\",\n",
       "        \"#918597\"\n",
       "    ],\n",
       "    \"series\": [\n",
       "        {\n",
       "            \"type\": \"candlestick\",\n",
       "            \"name\": \"kline\",\n",
       "            \"data\": [\n",
       "                [\n",
       "                    16.81,\n",
       "                    16.79,\n",
       "                    16.93,\n",
       "                    16.53\n",
       "                ],\n",
       "                [\n",
       "                    16.79,\n",
       "                    16.69,\n",
       "                    16.81,\n",
       "                    16.52\n",
       "                ],\n",
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       "                \"2022-01-27\",\n",
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   "source": [
    "## classwork 3\n",
    "\n",
    "* 分布用两种方式做出中国联通的20日均线和10日均线图\n",
    "\n",
    "* 在pyechart的图中把两个均线图叠加到之前的k线图中去"
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